Spatiotemporal Variation, Driving Mechanism and Predictive Study of Total Column Ozone: A Case Study in the Yangtze River Delta Urban Agglomerations

Abstract

Total column ozone (TCO) describes the amount of ozone in the entire atmosphere. Many scholars have used the lower resolution data to study TCO in different regions, but new phenomena can be discovered using high-precision and high-resolution TCO data. This paper used the long time, high accuracy, and high-resolution MSR2 dataset (2000−2019) to analyze the spatial and temporal variation characteristics of TCO over the Yangtze River Delta Urban Agglomeration to explore the relationship between the TCO and meteorological and socio-economic factors. The correlations between the TCO and climatic factors and the driving forces of meteorological and socio-economic factors on the spatial and temporal variability of TCO were also analyzed, and different mathematical models were constructed to fit the TCO for the past 20 years and predict the future trend of the TCO. The results show the following. (1) The TCO over the study area exhibited a quasi-latitudinal distribution, following a slight downtrend during 2000−2019 (0.01 ± 0.18 DU per year) and achieved its maximum in 2010 and minimum in 2019; throughout the year, an inverted V−shaped cycle characterizes the monthly variability of TCO; TCO was significantly higher in spring than in summer and autumn than winter. (2) Precipitation and the absorbed aerosol index (AAI) had critical effects on the spatial distribution of TCO, but meteorological factors were weakly correlated with the annual variation of TCO subject to the game interactions between different external driving factors. The monthly changes in the TCO were not in synergy with that of other meteorological factors, but with a significant hysteresis effect by 3–5 months. Socio-economic factors had a significant influence on TCO over the study area. (3) The Fourier function model can well describe the history and future trend of the annual TCO over the study area. The TCO over the study area shows a fluctuating upward trend (0.27 ± 1.35 DU per year) over the next 11 years. This study enriches the theoretical and technical system of ozone research, and its results can provide the necessary theoretical basis for ozone simulation and forecasting.

Study of Time-Frequency Domain Characteristics of the Total Column Ozone in China Based on Wavelet Analysis

“…et al [7] quantified the vertical ozone variability at different time scales using ozone data from Dobson measurements in the downtown Beijing and Xianghe suburban areas and found that the ozone single-peak and Dobson-based total column ozone exhibited consistent sinusoidal monthly variations, with a maximum value of 380 Dobson units (DU) in March and a minimum value of 305 DU in October. Based on the global TCO data of a global multi-sensor reanalysis (MSR2), Zhou, P. et al [8] studied the temporal and spatial variation characteristics of TCO in the Yangtze River Delta region of China from 2000 to 2019 and the correlation between it and related meteorological factors, populations, and industrial output values. They found that TCO is significantly higher in spring than in other seasons and the correlation between annual changes of TCO and meteorological factors is weak, indicating that it is affected by the game interaction of different external driving factors.…”

“…The correlation coefficient for the TCO and sulfur dioxide emissions reached 0.59 and the correlation coefficient for nitrogen oxide emission reached 0.60. (8) This study used the SARIMA model to predict the TCO of China. Considering the seasonality and other characteristics of the data, the data were pre-processed and then trained with the AIC information criterion to find the best model parameters.…”